This disclosure relates to translating content for display to a user. Translation is needed in many contexts, for example translations of applications, websites, and other digital content intended to be used in multiple countries or region. In order to be understandable in another language or region the content may need to be translated into another language, and word choice or layout may need to be adjusted to adapt the content for another region, even if the contextual meaning of the content remains the same.
Manual translation methods can be slow and prohibitively expensive to translate or localize content into many contexts; therefore current content translation methods may use statistical translation methods to generate translations for display. However, current statistical translation methods focus on generating grammatically correct or “word-for-word” translations which can lose some of the original meaning of the content. For example, a word-for-word translation can miss nuances in word choice or phrasing needed to preserve the original meaning of the content. Therefore there is need for a less grammar-based translation method better able to capture the underlying meaning of content in translations.